Kyle Bojanek

This study shows retinal population codes adjust their predictive timescale to input temporal structure using the information bottleneck framework.

The paper investigates how retinal ganglion cell activity can be compressed while preserving predictive information for downstream brain areas.

The paper analyzes retinal ganglion cell activity to show how sensory population codes balance normative optimality with variability through stiff and sloppy modes.

The paper analyzes retinal population codes in natural scenes to show that stimulus-invariant population structure contributes to scene identity encoding.

The paper constructs spiking neural network models to show that cyclic transitions between triangle motifs are necessary for sustained activity in sparse, asynchronous networks.